Every year the NIH-sponsored physiological data resource, PhysioNet runs a competition to solve some of the outstanding problems in physiological monitoring.

This year's challenge was won by a group of students at the Institute of Biomedical Engineering, mentored by Dr Gari Clifford, a lecturer in Biomedical Engineering, and Dr Andrew Kramer, Senior Research Scientist at Cerner Corporation. Cerner, a leading medical informatics company based in the US, also sponsors one of the team.

This year's challenge was to build an algorithm to predict outcome for individuals in the intensive care unit. Such an algorithm can help identify patients who are at risk, need extra (or changes in) treatment, or to help discharge patients early who no longer require treatment (thus reducing their exposure to infections and saving resources for more needy patients).

Dr Clifford's team of students, taken from the Centre for Doctoral Training in Healthcare Innovation, and the Systems Biology Doctoral Training Centre, developed the winning entry. This also happens to be the subject of the three of the students' theses.

Alistair Johnson (center) accepting the prize on behalf of the the Oxford team from George Moody (left) of the Laboratory for Computational Physiology at MIT. The other members of the team were Nic Dunkley, Louis Mayaud, Athanasios Tsanas, Andrew Kramer and Gari Clifford.